Advise Adapt Analyse Acquire ESCWA DATA STRATEGY INSPIRED BY THE 2020-2022 DATA STRATEGY OF THE SECRETARY-GENERAL OF THE UNITED NATIONS VISION ESCWA, an innovative catalyst for a stable, just and flourishing Arab region MISSION Committed to the 2030 Agenda, ESCWA’s passionate team produces innovative knowledge, fosters regional consensus and delivers transformational policy advice. Together, we work for a sustainable future for all. Economic and Social Commission for Western Asia ESCWA DATA STRATEGY INSPIRED BY THE 2020-2022 DATA STRATEGY OF THE SECRETARY-GENERAL OF THE UNITED NATIONS UNITED NATIONS Beirut Modernizing data systems and processes for management and administration at ESCWA 2 © 2021 United Nations All rights reserved worldwide Photocopies and reproductions of excerpts are allowed with proper credits. All queries on rights and licenses, including subsidiary rights, should be addressed to the United Nations Economic and Social Commission for Western Asia (ESCWA), email: publications-escwa@ un.org The findings, interpretations and conclusions expressed in this publication are those of the authors and do not necessarily reflect the views of the United Nations or its officials or Member States. The designations employed and the presentation of material in this publication do not imply the expression of any opinion whatsoever on the part of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Links contained in this publication are provided for the convenience of the reader and are correct at the time of issue. The United Nations takes no responsibility for the continued accuracy of that information or for the content of any external website. References have, wherever possible, been verified. Mention of commercial names and products does not imply the endorsement of the United Nations. References to dollars ($) are to United States dollars, unless otherwise stated. Symbols of United Nations documents are composed of capital letters combined with figures. Mention of such a symbol indicates a reference to a United Nations document. United Nations publication issued by ESCWA, United Nations House, Riad El Solh Square, P.O. Box: 11-8575, Beirut, Lebanon. Website: www.unescwa.org 3 Executive summary The present ESCWA data strategy supports the mandate of the Economic and Social Commission for Western Asia (ESCWA) to better utilize local, national and regional data sources. It aims to adapt the 2020-2022 Data Strategy of the Secretary-General for Action by Everyone, Everywhere to the ESCWA context, by designing and deploying an organizational data framework, fostering statistics and data analytics, and building synergy among organization-wide data activities, portals and projects. The ESCWA data strategy articulates a vision and mission based on the analysis of the organization’s data gaps (gap analysis via the fishbone approach), and accordingly scopes the following four critical work areas: statistical data; data analytics; data management; and data platforms. It details these four work areas according to the respective strategic drivers to derive a high-level operational action plan for the way forward in implementing the strategy. Moreover, the strategy underlines five enablers, or implementation requirements, to support the effective implementation of the work areas, while simultaneously encouraging and enabling ESCWA staff members to bring innovative data application ideas to their work. Feedback on the strategy was solicited from the various ESCWA clusters and staff members. The strategy calls for the formation of a data strategy action group at ESCWA to oversee the implementation of ESCWA data initiatives, and coordinate with the wider statistics and data community of the United Nations system. This group will operate under the framework of the United Nations Data Governance Group to execute the strategy via various activities that resonate with the Data Strategy of the Secretary-General. The document is not intended to be prescriptive or exhaustive, and recognizes the demarcated nature of ESCWA clusters, offices, units and teams. It leverages data use and information sharing for a more agile organization to better serve member States. Contents ______________________ 3 Executive summary 5 1. Value Statement 5 A. Vision 5 B. Mission 6 C. Goals 6 D. Principles 7 2. Methodology and Analysis 7 A. Drafting process 8 B. Related work 8 C. Data gap analysis 10 D. Scope 11 3. Work Areas 11 A. Statistical data 14 B. Data analytics 18 C. Data management 20 D. Data platforms 21 4. Strategy Enablers 21 A. Technology 22 B. People and culture 25 C. Budget requirements 25 D. Data governance and oversight 27 E. Partnerships 28 5. Required Actions 29 6. Strategy Deliverables 30 Annex I. Examples of ESCWA statistical and inter-regional cooperation activities 33 Annex II. Suggested ESCWA high-level modelling governance framework 34 Annex III. High-level Data and Technology Ecosystem 35 Annex IV. ESCWA data solutions 36 Annex V. High-level operational action plan 37 Annex VI. Terms of reference of ESCWA data privacy and security roles 38 Endnotes 5 Value statement _________ A. Vision ESCWA values data as a strategic asset needed to address the complex sets of development challenges in the Arab region. To deliver on its promise of shared prosperity and dignified lives for all the people in the region, ESCWA must strengthen data capacity for policy analysis and support. To that end, the vision of the ESCWA data strategy is: ESCWA as a data-driven think tank acting in synch with the whole United Nations data ecosystem, to deliver evidence-based policy analysis, advice and advocacy to support policymakers in the Arab region. B. Mission The mission of the ESCWA data strategy is set to implement the ESCWA data vision in an optimized and effective manner, in line with the core values of the United Nations and its new development vision, embodied in the 2030 Agenda for Sustainable Development. To support government policymakers and stakeholders through effective and customized policymaking capacity for a prosperous Arab region, the ESCWA mission would be: The strategy intends to develop, harness and sustain data activities beyond basic statistical work, which is a subset of the more comprehensive data ecosystem. The vision and mission of this strategy are inspired by models, tools and methods set out in the Data Strategy of the Secretary-General. To harness ESCWA human and technological resources to utilize data as a strategic asset and enabler to enact evidence-based development policies, strategies and programmes in the socioeconomic fields. 6 C. Goals • The strategy aims to achieve the following objectives: • Stock-take data sources of concern to ESCWA data users • Map data resources with current and future needs of ESCWA • Deploy state-of-the-art data technologies for improved policy advice • Synergize data sources with analytical models and platforms • Promote the use of data visualization tools and approaches • Enrich data-related jobs and skills at ESCWA to better utilize the data stock at ESCWA and elsewhere • Introduce sustainable measures to protect data in stock and transit • Improve data and statistical services provided to national statistical offices in ESCWA member States • Become an active node on the data and statistical ecosystems and an active pillar in the broader United Nations system • Ensure regular updates of data and statistics and their reliability • Apply organization-wide data quality frameworks and standards for core data assets. D. Principles The following principles guide the present strategy document: • It supports the Data Strategy of the Secretary-General • It covers both technology-generated data and classical data, be it open data or big data, and statistics • It outlines security, privacy and ethical concerns guiding data governance • It addresses data, particularly open data, as a foundation for information or knowledge • It applies a bottom-up approach where all relevant ESCWA stakeholders are involved and encouraged to develop data use cases. Due to the changing nature in the data and technology paradigms, the duration of strategy implementation will be open-ended. It is not determined in the strategy document but will be set out in the implementation action plan. 7 Methodology and analysis _________ A. Drafting process Several competing methodologies exist for building and implementing any strategy. The top-down, bottom-up and iterative processes are prominent approaches. This strategy adopts the iterative process, a cornerstone of Agile practices for data-driven cases relying primarily on technology, in particular information and communication technologies (ICTs). The Acquire, Analyse, Adapt and Advise cycle was adopted based on the relevant literature related to each of the work areas identified by the strategy and depicted in figure 1. Figure 1. ESCWA data strategy building process Acquire relevant work Analyse consulted work Adapt to ESCWA and to users Advise specific recommendations These development facets conform with the well-established Plan, Design, Check and Adjust (PDCA) cycle, as follows: Plan: Acquire relevant work. In this event, specific work areas are approached individually, and relevant literature and guidelines from the United Nations and the private sector are collected. This will produce the backlog required for the next iteration. Design: Analyse the collected literature. The backlog is narrowed down according to the scope of the strategy. This stage may be re-visited according to new insights solicited from stakeholders. Check: Adapt the knowledge to the ESCWA landscape. To effectively translate theory into practice, this step ascertains whether the selected activities resonate well with the ESCWA environment and aspirations. This step is dynamic, allowing for future amendments according to further input and review. 8 Adjust: Advise custom-tailored recommendations. Tangible recommendations are put forward that will guide the activities in the execution action plan. This step integrates the knowledge and adjustments determined in the previous steps. B. Related work Data and knowledge production, processing, sharing, and taking action represent the bedrock of the United Nations added value in support of its mandate. Data is therefore considered a strategic asset to realize the full potential of the United Nations, especially during the ongoing system-wide reform. As ESCWA aspires to support member States in achieving the SDGs via data insights, informed policy advice, and innovative development solutions, the present strategy is based on relevant United Nations work and relies heavily on the Data Strategy of the Secretary-General and other data-related policy documents and guidelines. Relevant operating strategies that influenced the development of the present strategy include the following: the Data Strategy of the Secretary-General for Action by Everyone, Everywhere (20202022); the United Nations Geospatial Strategy (2021); the ESCWA Innovation Strategy (2020); and the ESCWA Digital Strategy (2021). Other United Nations policy documents and guidelines were also utilized, including the Systemwide Roadmap for Innovating United Nations Data and Statistics (May 2020); the United Nations Principles of Official Statistics; i-Seek Information Management Generic Job Profiles; the ESCWA Statistical Framework; the UNIN Annual Innovation Capacity Survey; and the Memorandum for the Data Strategy Implementation. C. Data gap analysis To have a 360-degree perspective of the data status at ESCWA, it is critical to provide an assessment of the current data situation and frame the data gaps that exist at ESCWA. Data gaps or challenges represent items that are missing and those that are redundant. Both missing and overlapping data will hinder the production of sound policy analysis or advisory work. Data management challenges include data discrepancies and errors, scattered data cleansing efforts, and latency in data production where in some cases data produced will go to the shelf or be declared useless on arrival. Considering priority ESCWA data use cases, the data lifecycle – collection, storage, and use – is often completed in silos; consequently, data are frequently used to serve a single use at a particular time. From a governance perspective, data collection and processing can produce broken time series, multiple sources and references, resulting in blurred data generation outcomes, with storage, retrieval, and dissemination problems. It is evident that data use is a pressing need, especially in a volatile region such as the Arab region. 9 Such issues may be homegrown at ESCWA and/or are embedded in the imported data from outside. It is observed also that external data has its own bottlenecks and handicaps, which pose a threat to the quality of data utilized locally at ESCWA. These gaps (internal and external) will restrict the organization’s ability to leverage data to produce good analytics. The root causes of ESCWA data gaps are traced to: • Uneven data cultures, skills, and capabilities. • Inadequate technology environments. • Lacking a data governance paradigm. This indicates an array of internal data challenges at ESCWA (figure 2) that constrain the optimal utilization of data in the below-mentioned data use cases. Moving forward, ESCWA needs to address the root cause of the organizational data gaps and issues, and not only remedy the symptoms. Data gaps are therefore further broken down according to the scope of the present strategy. Figure 2 lists common organizational gaps for data at the stages of acquiring, processing, analysing, and disseminating. In a general outlook, ESCWA data issues include data-related legacy technologies and databases at the core of existing data programmes, restricting holistic data sharing and secured utilization. This gap analysis demonstrates that the present data strategy will make new demands on staff members and the skill set they possess, showcasing a necessity to facilitate digital transformation through training, hiring and business process re-engineering. Moreover, it is evident that ESCWA Figure 2. ESCWA data issues mapped in a fishbone diagram Acquiring Data Management Data Sources Npoociunrtaotfioennatrty Diasusctoohunoinrrceitecysted Trsatddaaitttiisaotnicaal l Data Structure Tools Data Stewards Lopnrogcesses Vadrafiootarums ats Indcahotahanedreenlint g Dadteoacvaeyritnimg e Processing Wemaektadata OuRrtIeenddgdaadaiucotatencnatdudaaral adntateta Display raw data feBaatsiurcevsisualization feRaetpulirceasting existing gSovpeorranadinccewistthruncoture maonWdaleelyastkicuatlilidzaattiaon of mCoednetlrsalized data dLaitamitaendalynsutsmber of prbaeNcsottischeasring of daNtoaliinniktiinatgivsiesmilar Models Teams Analyzing Platform Disseminating Ladcoakwtaonfers Abosfeendngactinaeeers Unwftiaothmolnsileiawrity Letegcahcnyology ESCWA DATA GAPS 10 lacks new and diversified data stores, including cloud and data lakes and warehouses, and does not pay the necessary attention to the security dynamics, which change significantly alongside these products. In this regard, it is observed that ESCWA should go beyond protecting the perimeter of a data centre, especially with the increase in various types of cyberattacks. Similarly, best practices are not fully deployed for data curation at the point of entry (e.g., surveys) and for data decaying over time, alongside poor metadata management (e.g., different teams tagging data differently). Lastly, with expanding data-driven decision-making, analytics are relatively distanced from core ESCWA business definitions and management visions. D. Scope The present strategy aims to provide better data servicing to member States, and a more coherent “One UN” data approach for efficient United Nations work in the Arab region. It should be used by all ESCWA staff members to streamline data handling behaviour at various levels and functions, such as data literacy and official statistical reporting. The strategy addresses data in its various forms as a statistical resource; digital and information knowledge asset; and a visualized decision-making tool. The time validity of the strategy is conceptually open-ended, reflecting the timeframe and deadlines put forward by both the United Nations Data Governance Group steering the implementation of the Data Strategy of the Secretary-General, and the suggested roadmap and incremental updates of the Chief Executive Board for Coordination (CEB). 11 Work areas _________ Data is a strategic resource for modern knowledge-powered organizations. Quality information and knowledge are instrumental for policy and decision-making, and must rely heavily on the production, processing and dissemination of accurate, timely and relevant data. The challenge is that decision makers are either deprived from any data in certain critical areas, or bombarded in other areas with large quantities of data from multiple sources with different attributes and quality dimensions. In many cases, too much data, and even in certain cases inconsistent data, could be as useless as too little data. Moreover, data and information come in different formats and layers of sophistication. One challenge, for example, is to decide whether to use data from internal ESCWA repositories, external sources from Arab countries (national statistical offices or others), or the broader United Nations system, because of the lack of similarity and interoperability, and the numerous data gaps when solely using national data. To tackle this complex endeavour and not overlook important data policy issues, the present strategy addresses the topic on a modular basis, under the following work areas. A. Statistical data The present section categorizes statistics as a subset of data and addresses the statistical priorities, strategic goals, opportunities, challenges and partnerships needed for policymaking in the Arab region and within the United Nations actionable priorities. It highlights interagency and intergovernmental statistical coordination and collaboration in the Arab region, and related activities such as data and statistics on the SDGs. Moreover, with the increasing integration of technology in official statistics, as evidenced by the already high level of utilization of electronic data collection in censuses and surveys, this section also considers the increased utilization of non-traditional data sources (e.g., remote sensing and geospatial technologies, big data, and register-based data) in the Arab region’s official statistics. More specifically, regional statistics need to be approached at the sectoral statistical development level, including statistics related to conflict repercussions, population and housing censuses and household surveys, civil registration and vital statistics, social indicators, integrated economic statistics, prices and financial statistics, transport statistics, gender statistics, statistics on persons with disabilities, development indicators (taking into account global and regional frameworks of indicators), urban development statistics, environment statistics, and environment economic accounting. Therefore, the present strategy covers the respective mandates and guidance of the ESCWA Statistical Committee, the leading intergovernmental body for statistics in the Arab region, and the needs identified by the Regional Working Group on Data and Statistics via the interagency coordination mechanism. 12 Lastly, the strategy presents an overview on the coordination and harmonization efforts among the five statistics divisions of the United Nations regional commissions and the United Nations Statistics Division, the implemented coordination mechanism, and the achievements of this collaboration, especially the harmonized presentation and interpretation of SDG statistics and indicators. Aligning the Arab statistical activities with the United Nations Data Strategy ESCWA statistical activities are part of the subprogramme on statistics, information society and technology implemented by Cluster 4, in close collaboration and coordination with other clusters. ESCWA responds to the two key United Nations data-related strategies in an integrated way, notably to the Data Strategy of the Secretary-General targeting mainly internal processes and to the CEB System-Wide Roadmap for Innovating United Nations Data and Statistics to provide coordinated support to member States. The approach builds on top of the “localized” roadmap of the CEB by amending its recommended set of activities to reflect the ESCWA landscape, as summarized in figure 3. Figure 3. Local initiatives as inspired by the CEB localized roadmap Data Strategy by the Secretary-General for Action Everyone, Everywhere People and culture Environment and infrastructure Data assets and use Data protection and privacy CEB System-Wide Roadmap for Innovating UN Data and Statistics Target 1.1 New data sources Target 1.2 Adequate skills New methodology and technology Target 1.3 UN Data Portal Target 1.4 Ethical Standards Target 2.1 Culture of data literacy Target 2.2 Predictive analysis, nowcasting, forecasting Modermizing data systems and process for management and administration at ESCWA TC workshops and advisory services on Big Data readiness assessment Recruiting . Data scientists . GIS specialists Big data internal training Generic law of official statistics (in Arabic) Statistical Capacity Development . Knowledge . Skills . Competencies Big data projects . Telecom data . Social networks . Sentiment databases Geospatial information . Remote sensing . Georefrencing Intern-regional coordination statistics . SDG harmonization . Collaborating platforms . Data strategy implementation ESCWA Data Management System ESCWA Data Portal . ESCWA Data Portal . Arab SDG monitor . Arab SDG Gateway . Regional GIS platform . SDG National Reporting Platforms Potential open data sharing and dissemination by ESCWA . Principles Governing International Statistical Activities . Fundamental Principals of Official Statistics . TC activities with EMCs Statistical Capacity Development . Institutional setup . Organization platform Thematic data issues (with a simple graph/ chart and a brief story) prepared by data scientists Statistical Capacity Development . Legal framework Estimates for missing values for the recent years Nowcasting for the latest year Global Geospatial Information All applications for statistics Management UN-GGIM - Arab region Electronic data interchange 13 Regarding the harmonization and sharing of United Nations statistics and data, ESCWA will continue participating in the Committee of Chief Statisticians of the United Nations system and global working groups on statistical methodologies, such as the Inter-Agency Working Groups on National Accounts on SDGs, and the High-Level Group on Partnership, Coordination and Capacity Development. ESCWA will ensure full alignment with global statistical standards, to maintain high quality and reliability of data and the trust of regional partners and national statistical offices. This work will take place in close collaboration with the United Nations Statistics Division, other regional commissions, and the statistical units of specialized agencies. The knowledge and experience acquired through the global working groups will be transferred by ESCWA statisticians to the Arab region. ESCWA will ensure data integrity and consistency across various knowledge products produced by ESCWA, as a key element of data management and dissemination. The Data Portal will be used as a unique data source for other knowledge products containing statistical data, with its content maintained in line with the Fundamental Principles of Official Statistics and the Principles Governing International Statistical Activities, based on national data sources and data from custodian agencies within the United Nations system. Data gaps will be resolved through reliable sources and/or appropriate estimation techniques (nowcasting/forecasting). For each data domain published through the Data Portal, ESCWA will prepare a guide for estimating missing data, especially for the most recent years. Accordingly, ESCWA will minimize gaps to a reasonable level and eliminate discrepancies and unreliable data sources, while guaranteeing that the Data Portal is consistent with data released by custodian agencies within the United Nations system and by United Nations Headquarters. Collaboration in statistics and data is at the heart of the regional reform of the United Nations development system, and is based on the following two established mechanisms: the Task Force on Data and Statistics of the Regional Cooperation Platform that involves regional offices of United Nations agencies under the leadership of ESCWA and UNFPA; and ESCWA participation in the data and statistics working groups of the United Nations country teams, especially in the provision of data for common country assessments, assistance in SDG reporting and tight coordination in the provision of technical advisory services in the field of official statistics. To that end, the SDG national reporting platforms that ESCWA is establishing in partnership with national statistical offices will streamline simpler and consistent data flows between Arab countries and the United Nations agencies. In this regard, ESCWA recognizes the Data Strategy of the Secretary-General in many dimensions, especially on modernizing data systems and processes for the management and administration of ESCWA. Efforts are needed to increase the knowledge and skills of staff members in data science, technology for statistics, geospatial information systems, big data, and other progressive topics. It is also necessary to enhance ESCWA statistical capacity to better handle internal and external data, and to advise member States and intergovernmental processes. 14 Dimensions of statistical work ESCWA action related to data and statistics involves the work undertaken in collaboration with national statistical offices and national statistical systems, and with other United Nations and regional organizations active in official statistics in the region, thus covering internal needs for data and statistics. There are three priority areas of intervention, as follows: Services to national statistical systems. This needs to be conducted under the guidance of the Statistical Committee. It focuses on the needs of national statistical offices and consist of bilateral and multilateral activities. Multilateral activities (regional and subregional) include work on statistical methodologies, such as methods and data sources for disability statistics, the inclusion of Islamic banking in the System of National Accounts, civil registration and vital statistics estimates, use of administrative data sources, pilot projects on big data, use of advanced technologies in statistics, and linking statistical and geospatial information. Regional cooperation. It entails both multilateral cooperation involving national statistical systems facing similar challenges, and direct assistance based on requests addressed to ESCWA. Relevant activities address the skills, knowledge, competencies, legal framework, institutional setup, and organizational platform. ESCWA, in collaboration with relevant partners, has developed several tools, such as the generic law of official statistics, online training tools, handbooks and guidelines. Bilateral activities build on a specific situation of each of the countries involved, and aim to generate practical solutions and new data that were not previously available. Collaboration with specialized regional organizations. This includes ESCWA commitments to the Regional Coordination Platform and the United Nations country teams. ESCWA also collaborates with regional and global offices, such as the Arab Institute for Training and Research in Statistics (AITRS), the Statistical Centre for the Cooperation Council for the Arab Countries of the Gulf (GCC-Stat), the Arab Industrial Development and Mining Organization (AIDMO), the Statistics and Database Department of the Leagues of Arab States, the Gulf Organization for Industrial Consulting (GOIC), the Data-Pop Alliance, and the Qatar Computing Research Institute. A sample of previous ESCWA inter-regional cooperation activities on statistics and data are showcased in annex 1. B. Data analytics One of the core activities of ESCWA is data analysis. This work area of the strategy sets out the analytical capacity of data at ESCWA, and how it can be improved via concrete steps that address the current ESCWA modus operandi. A strategic focus is on data analytics of high relevance to priority policy areas of ESCWA work programmes, which have the potential of producing tangible results for Arab countries and the region. Data analytics can range from simple arithmetic analysis conducted by a single staff member, to sophisticated modelling and simulations by groups of analysts. The below subsections discuss the relevant analytic areas and recommend a high-level data modelling framework. 15 Data modelling Models are used at ESCWA to produce forecasts, scenarios and policy options, mostly based on demand or to satisfy a project requirement. Sometimes models have been utilized based on supply (ESCWA push) or on staff loyalty to models they acquired from academia or previous work at other organizations. Furthermore, data modelling practices at ESCWA have been practiced mostly in silos, owned and operated by a particular researcher or a team of researchers, and often missed an opportunity to benefit from the expertise of other colleagues outside the team. In other words, data modelling at ESCWA is not a regularized practice and does not follow a framework or a clear governance structure that enables cross-functional team collaboration and procuring new models. Therefore, the third stage in the data management life cycle (data analysis) can be enhanced by developing an ESCWA model base. Any staff member at ESCWA can access and look up models registered at the model base. If an existing model can be utilized for an ongoing project, project coordinators can request the model through the appropriate channels to guarantee unrestricted access to their team. In addition, if after consulting the model base the needed model is not present, any staff member can contribute to the model base by filing a proposal with the project coordinator. For optimal results, teams involved in data analytics will comprise statisticians, data scientists, and policy experts. Teams will take advantage of all relevant data from ESCWA datasets, big data, registration systems, and geospatial sources. At the cluster level, a coordinator for data analytics will be appointed to liaise with coordinators from other clusters. At the project level, this approach complements the data analytics skills needed by inter-cluster teams for data modelling exercises. Project coordinators will be the bridging point between ongoing data projects and the cluster coordinator. This will increase the efficiency of resource utilization by avoiding duplication of efforts and benefiting from skills already present internally. Table 1. Proposed template for an ESCWA model base Model name Description Use cases Model steward References With this background, this Strategy stipulates that the modelling practice in ESCWA clusters and units needs to be netted together via the model-base framework or platform. However, this netting via a framework or a platform should not be seen as an attempt to centralize modelling services at ESCWA, or create a special unit for it. The project teams will be fully empowered, and a smart model-base should be created for wider utilization and agility. Annex 2 presents the proposed flowchart of the high-level modelling governance framework. As shown in the framework, data modelling practices are still owned by the modeler at ESCWA, but is open for other staff members to utilize within their projects. Similarly, this framework ensures the model base is constantly updated by ESCWA staff members with various models, and supports the full spectrum of analytics (descriptive, diagnostic, predictive and prescriptive). 16 Geospatial data Data can take the form of geographic linkages. Geographic data is increasingly recognized in policymaking. ESCWA should encourage more reliance on such technology-based data and location-based data services. It is needed for decision and policy making within internal ESCWA work and in service of member States. As the mandates of United Nations agencies cover a wide array of activities, there is no one-size-fits-all policy for Geospatial Data. As such, the United Nations Geospatial Strategy recognizes the specialized nature of each entity – their respective mandates and functions and the need for an operational autonomy to address specific mandates – and allows organizations to steer the Strategy’s implementation according to their scope of work. ESCWA has been utilizing GIS and geospatial use-cases in its substantive and operational work, however, it is considered islands of excellence with no comprehensive framework for organization-wide utilization. With regards to countries, ESCWA is in the business of enhancing GIS services in national statistical offices of member States. Other uses may exist sporadically. ESCWA will expand the traditional view of the geospatial technologies and primarily maps with linked data used for presentation purposes. This expanded framework for geospatial data at ESCWA comprises the following: • Remote sensing and use of satellite imagery to generate new types of data (additional data, detailed geographic granularity, avoiding costs of surveys, etc.); • Expanding the traditional data analytics focused on temporal analysis (long time series) to spatial analysis (comparing small geographic areas, determining the geographic areas); • Participating in the regional geospatial data portal, in collaboration with other United Nations system agencies active in the Arab region; • Utilizing multi-layer interactive and dynamic maps for ESCWA data and analytical products. This Data Strategy primarily considers the second goal of the UN-wide Geospatial Strategy related to enhancing innovative geospatial and analytics services in support of useroriented and problem-solving for enhanced mandates delivery. In specific, geospatial data is considered as a case-specific analytical tool to meet policy needs without approaching it as a standalone work area, and prioritizing the substantive activities outlined in the work of the Committee of Experts on Global Geospatial Information Management (UN-GGIM). Moreover, ESCWA will engage in partnerships with the wide geospatial community, comprising both sister United Nations organizations and member States, towards the open sharing of geospatial data and the respective analytical tools. To that end, ESCWA must consult existing coordination networks such as the United Nations Geospatial Network to establish partnerships as appropriate and establish a key role in the wider United Nations data ecosystem. 17 Figure 4. Geospatial data framework at ESCWA Data Input Data Analytics Data Presentation Policy Briefs Satellite images AI for image processing Remote sensing Spatial (geospatial) data analysis Interactive maps Small areas data Determining areas with common characteristics Dynamic (time related} maps Multi-layer maps Interactive dashboards Mobile Apps Raw geospatial data from external sources Combining temporal and spatial analysis User-customizable map output Publications According to the United Nations Geospatial Strategy, ESCWA, as a regional economic and social commission, is instrumental to facilitate partnerships with greater emphasis on local representation by a federated approach across geography and theme. To put into actionable terms, ESCWA needs to utilize the following strategic pathway: 1. Stock-take GIS services utilized at ESCWA and create internal awareness about its capabilities and use-cases at ESCWA. 2. Encourage the production of GIS-based reports and other products at ESCWA for policy support. 3. Engage and develop with stakeholders in member States to increase the availability of public data, and eventually deploy a geospatial data ecosystem for policy support. 4. Support member States in the form of technology transfers, capacity-building, and operational concepts with UN-GGIM thematic networks. 5. Raise awareness and conduct communication campaigns to promote transparent geospatial information management. 18 C. Data management Data lifecycle Driven by the urgency and ambition of the “Decade of Action”, the Secretary-General has recognized that data are a strategic asset for the United Nations system. As a result, the United Nations pursued an ambitious agenda in lockstep with other structural United Nations reforms via initiatives that are designed to nurture cross-cutting capabilities and eventually facilitate data-driven decision-making. The current data lifecycle at ESCWA includes data generation, storage, retention, dissemination, and maintenance. To effectively deliver on the vision of the Data Strategy of the Secretary-General, ESCWA is to scale up this traditional data lifecycle to include policies, processes, and standards for the effective analysis of data. To deliver on this promise, the strategy aspires to apply the right mix of data, people, tools and governance by adopting the ESCWA data architecture presented in figure 5, hereafter referred to as the “data ecosystem”, which builds on the “value chain in analytics” of the SecretaryGeneral’s Data Strategy by adding a data marts stage. Figure 5. ESCWA data architecture for generating data insights Identify proper data sources Extract, transform, and load Storage, data warehouse Data marts and areas Analytics and vizualization Dissemination outlets This architecture is not meant to be a substitute for the current data lifecycle at ESCWA; instead, it streamlines the well-established first four data lifecycle stages (i.e., data generation, storage, retention, and maintenance stages) to create data that can lend itself to generating insights. As such, this architecture leverages data pre-processing and processing by adding the fifth stage: analytics. The analytics stage will serve as an extension to the traditional data stages at ESCWA to contribute at the dissemination stage with high business value. This data architecture is meant to be modular meaning that each area can stand alone on its own merits and can have its owner/custodian. An individual project may take specific modules of this architecture in line with their scope (expected results, input data, etc.). Without this data architecture, the same data problems might emerge in many different projects and data will tend to be duplicated in various use cases. In specific, the goal is to feed the increasing data-driven ESCWA products with a unified and structured repository as discussed in the following section Data Platforms. Fostering a pragmatic approach, the storage stage in the proposed data ecosystem will act as the organization’s Data Warehouse that will then be divided into data areas or clusters according to the data use case at ESCWA. As these ESCWA products are complementary, coherent, and possess high similarity in data areas, it becomes especially important to unify both the data and the respective dissemination outlets via this architecture. In brief, this data architecture decouples the data pipeline enabling the ESCWA stakeholders to develop innovative data use cases and think holistically across the organization’s boundaries while simultaneously articulate their vision with the technical experts. Annex 3 showcases examples of the data and technology ecosystem. 19 Data protection and privacy In line with the Data Strategy of the Secretary-General, the United Nations Data Governance Group steered by the Executive Committee established the data privacy and protection programme across the United Nations system. The result was the Secretary-General’s Bulletin (ST/SGB) on “Data protection and privacy policy for the United Nations Secretariat” which was reviewed by OIOS and relevant EC decisions (EC/2020/77). The ST/SGB formalizes the “2018 Personal Data Protection and Privacy Principles”, adopted by the HighLevel Committee on Management (HLCM), into the legal framework of the United Nations Secretariat. Consequently, the ESCWA data strategy is expected to help harmonize data protection and privacy efforts by participating in the overall United Nations Data Governance Structure in an independent and unique layer showcased in figure 6. Figure 6. ESCWA data protection and security organogram as part of the United Nations data strategy Executive Committee Chief Data Protection Officer Data Protection Committee Data governance Group ESCWA Data Controller/Steward Data Protection Focal Points Data Operators (Staff) Data Operators (Third Parties) It is important to recognize that data protection and privacy efforts will not succeed, unless policy improvements are synchronized with, and woven into, business processes, technology, people capacity, and culture. As such, to ensure effective implementation, oversight and accountability, the unique governance layer at the Secretariat department or office labels staff and partners as Data Processors and connects them to the wider United Nations data protection ecosystem via Data Protection Focal Points. The ESCWA data controllers/stewards ensure ST/SGB compliance as instructed by the Secretary-General by overseeing the purposes, content, use, and means of data processing in ESCWA. Such functionalities will be assigned to ESCWA data staff (discussed previously in the Data Skills section) and not introduced as standalone job posts. For example, Data Controllers ensure the processing of any personal data – information, in any form, that relates to an identified or identifiable natural person – by Data Processors for purposes consistent with ESCWA mandates and respecting the United Nations Universal Declaration of Human Rights. In this ESCWA data governing structure, focal points, in consultation with OIOS, are to identify – and where necessary cost – priority changes in organizational processes and practices and software applications used for programmes and operations. 20 Such significant improvements in data governance and organizational setups are to be complemented with updated data processing modalities. Primarily, ESCWA is to process relevant data fairly for specified and legitimate purposes as well as for limited retention periods. Moreover, special guidelines must be set in place during the processing of “nonpersonal data in a sensitive context”: that is, information which, while not relating to an identified or identifiable natural person, might put a vulnerable person or group at risk of harms (e.g., refugees from war-torn member States). Similarly, ESCWA is encouraged to allow these individuals whose personal data is processed to raise grievances via user-friendly and simplified channels. D. Data platforms At ESCWA, platforms have been utilized mostly for internal management processes such as supporting staff travel, issuing official documents, staff attendance, etc. More recently, data started to be utilized via platforms for use cases intricate to the ESCWA clusters scope of work. Hence, data platforms were introduced as one more innovative way to serve member States. This Strategy document addresses ESCWA data platforms as well. However, traditional approaches to data management including ad hoc data wrangling and isolated tools simply do not scale and a platform approach is required to reconcile all data from multiple data sources into a single, shared data management solution.1t Some of the ESCWA data platforms depend on the preference and prerogative of the data user creating data redundancies, data lags, and illreferencing. Some rely on a single source of data which makes a less mature platform that otherwise has the potential to modernize work processes. It is important to indicate that ESCWA has recently launched a dedicated data platform called the ESCWA Data Portal (EDP) showcased in annex 4. EDP is the prominent ESCWA platform catering for data and statistics for the national statistical offices in the Arab countries while the other data and informational platforms serve a specific goal or satisfy a certain request. The content of the Data Portal must be able to target users based on their attributes and needs and must also be continuously improved by resolving gaps and timeliness through estimations and nowcasting. Moreover, ESCWA efforts should be exerted on relying on statistical data from member States’ national statistical offices to produce quality data rather than to overlook them. This strategy proposes that data utilization by ESCWA clusters, and the associated projects, need to work as an integrated part of the ESCWA data architecture and not in silos or islands. To that end, ESCWA is to bring to operation IT solutions that have world best practices embedded in them and integrate them in a technology that uplifts the status quo and brings data utilization to a higher indifference curve. the data ecosystem framework, for example, was assessed as a viable framework utilized by noted international think tanks (such as the Harvard Atlas on Economic Complexity) to produce data visualizations greatly needed to produce policy alternatives. This consolidates the data platform for its sustainability at an institutional level. Besides, the accompanying ESCWA Digital Strategy complements this strategy by outlining the portal request process as part of an ICT committee that orchestrates all ESCWA platforms to ensure synergy. This committee will also directly oversee the procurement process of portals/platforms/technologies costing greater than $50,000. 21 Strategy Enablers _________ A. Technology In line with trends at the United Nations in general, the demand for better tools to acquire, manage, share, analyse and govern data is increasing across the organization. New technologies are constantly emerging and leading to more sophisticated capabilities. This rapid pace of change implies that particular technologies might turn out to be only a trend and may disappear quickly, raising doubts regarding their real practicality or impact. Furthermore, technology is not a solution to every problem at the organization. One size fit all should be avoided. Some contexts will not benefit from the use of technology and rather needs to be addressed from an organization behaviour point of view. Hence, implementing data technologies should not be the end goal of this strategy. Technology should be intertwined with the data processing needs. ESCWA is to assess breeds of technologies as enablers to realize a data use case with remarkable business value that serves the very mandate of ESCWA. The aforementioned data ecosystem framework is currently the most favourable solution as it provides world best practices on how to search and mine data for policy and decision making. More importantly, it is a highly modular steppingstone facilitating scalability and reuse toward more IT-driven but user-focused utilization of technology as shown in the below roadmap retrieved from the United Nations Innovation Network:2 Figure 7. Roadmap for ESCWA Data Transformation FOUNDATIONAL SYSTEMATIC TRANSFOMATIONAL Machine learning / AI Analytics Data foundations Ensuring you have good quality, discoverable and accessible data that is managed in a flexible scalable architecture Leveraging your data (on needs, risks, results and behavior) systematically to understand what happened, why it happened, etc. Building systems that can “learn” from data to deliver “intelligent” experiences and augment human capacity in processing and decision-making 22 The core data work at ESCWA follows a systematic model. Traditionally run by IT experts, the data ecosystem framework will manage ESCWA master data and increasingly enable self-service analytics as the demand for data querying, analysis, and visualization rises throughout the organization. New technology will prioritize the most common data analytics use cases at ESCWA, including the following: • Traditional reports, web-based platforms, and dashboards; • Advanced data modelling, forecasting, and simulation; • Big data and national statistics; • Crowdsourcing and in-sourcing. On the other hand, this Strategy does not recommend developing the technology solution in-house. After all, ESCWA mandate is not expected to serve as a technology provider. Instead, ESCWA is to focus on its fine work (modulated in clusters) and work closely with technology providers, foremost OICT, to develop the technology solution that will realize a data use case with pre-defined business value. This can be either contracting with leading companies or partnering with sister United Nations organizations all while considering licensing limitations and challenges. The following partnerships subsection provides guidelines as to when external partnerships are justified. ESCWA would also benefit significantly from artificial intelligence (AI) algorithms and machine learning (ML) that is based on big data and open data to produce analytics and extract insights from the data foundation. ML, AI, and other frontier technologies can provide support to ESCWA informed advice to member States by its ability to graze on large amounts of data from and about the Arab region. B. People and culture Workforce planning To meet the targets outlined in the Data Strategy of the Secretary-General, the United Nations agencies are expected to maximize existing data resources and identify the skills gaps. To that end, the Global Strategy and Policy Division introduced the Data Analytics and Management Job Family in Inspira creating 24 generic job profiles (GJPs) in the Professional and General Services categories, in the job groups of data engineering, data analysis, and data science:3 1. Data Engineer: Responsible for supporting everyone with data preparation, speeding up the creation of curated trusted data pipelines, and their integration. Figure 8. Workforce planning five-step methodology Identifpyrisotrriatiteesgic 1 5 dDeemfiannedtalent 2 repMoortniotnorparongdress 4 Develop plans to 3 close skill gaps Evalusautpeplyworkforce 23 2. Data Analyst: Responsible for collaborating with colleagues on data and analytics, including research, reports, visualization, presentation, dashboards, scorecards. 3. Data Scientist: Responsible for extracting deep insight from data and using complex models, employing statistics, algorithms, AI and visualization methods. The overall workforce planning is a five-step methodology meant to align workforce capabilities with the programmatic and strategic priorities, as shown in figure 9. Table 2 maps this process with the ESCWA landscape where the ‘strategy work areas’ column represents the organization’s strategic priorities, and the ‘data role’ column shows the required data role for the work area. The workforce supply currently considers employed staff and in the future, further enumerations are to encompass non-staff. Moreover, these generic job openings (GJOs) can be used immediately for all temporary recruitment purposes. However, the Executive Committee decision 2020/77 of 11 November 2020 requested departments to identify opportunities to reprioritize nonpost and post resources towards stronger data capabilities, including a focus on entry-level staff grades (e.g., P1, P2). Therefore, ESCWA has four possible tracks to reprofile current positions into data positions (step 4 in the methodology): 1. Reclassify selected existing data-focused positions using the new GJPs and job codes and go through the budget approval process. 2. Reclassify some existing non-data positions using the new GJPs and job codes and go through the budget approval process. It’s in line with the Controller’s guidance to use current vacant positions including upcoming retirements to fill the data skills gap. 3. Use the GJP for a temporarily existing position and pending the reclassification and budget approval. 4. Use an existing non-data position and incorporate some elements from the newly developed GJPs without changing the job family and with less than 30 per cent changes from the original classification document and advertise accordingly with the original job code and job profile. As such, the operational actions for ESCWA data staffing can be reclassification (identify the post as data-focused), classification (new posts or conversion), recruitment, reassignment, and reskilling and upskilling. These actions resonate well with the Secretary-General’s Data Strategy’s medium-term target to reach a ratio of 1 out of 10 (i.e., at least one data specialist among 10 colleagues) where data analytics will be incorporated across the competency framework currently under development.5 Training and capacity-building Training for data analytics and management has been identified in the Office of the Human Resources learning needs, creating learning paths for different levels of proficiency. Online 24 Table 2. ESCWA data roles needed to implement the data strategy Strategy work areas Data role Terms of reference Data protection and privacy • Data Protection Officer • Ensure ST/SGB compliance within the organization; • Designate entity data protection focal points by 30 June; • Oversee the purposes, content, use, and means of data processing in their entity or cross-cutting enterprise function; • Manage exceptions to data protection policies; • Facilitate the use of data assets within the organization. Data management • Data Engineer • Optimal extraction, transformation, and loading of data from a wide variety of sources into data pipelines; • Manage the identification, design, and implementation of internal process improvements: automating manual processes, optimizing data delivery; • Manage the implementation of changes to data systems to ensure compliance with data governance. Statistics • Identify appropriate data sources for analytics projects; • Develop and implement databases, data collection • Data Analyst systems, data analytics, and other strategies that optimize statistical efficiency and quality; • Identify, analyse, and interpret trends or patterns, using basic machine learning techniques, statistical methods. Data platforms • Data Engineer; • Predefined • Data Analyst. Cluster-specific • Data work areas Scientist • Mine and analyse data from organization databases to drive optimization and improvement of programme development, advocacy, and business strategies; • Develop custom data models and algorithms to apply to data sets; • Use predictive modelling to increase and optimize entity experiences. Analytical capability • Data team lead (senior data scientist) • Lead the ESCWA Teams that build systems delivering data-intelligent insight; • Develop systems that “learn” from data to augment human capacity in processing and decision-making. 25 learning collections have already been added to LinkedIn Learning for the United Nations under six categories: Analytics, basic data tools, and applications, nurturing a data culture, governance, data science and coding, and data management. With regard to data management, additional resources are referred to in the CEB roadmap, such as UNSSC, UN-SPIDER, IFAD, UNITAR and Space4Water. The project coordinators are only to designate a course quota to be completed by the workforce over a designated timeframe with their freedom to select the courses most suitable to their mandate and tasks. To succeed in that, ESCWA needs to improve staff data literacy skills across the whole of organization – eventually enhancing internal data compilation processes and ensuring collective understanding on data trends in general and big data in specific – by giving more voice and attention to young people – many of whom are naturally digital natives – to be part of leveraging data insight into practical action via digital technology. C. Budget requirements Implementing this strategy and the derived action plan requires an extra budget to cover the following: 1. Enhancing technology infrastructure. 2. Training and capacity-building. 3. Conducting job classification and reclassifications. 4. Optimizing tendering and procurement procedures. 5. Partnering with other agencies. A budget envelope for implementing the strategy is generally not proposed in a strategy document. Instead, budgeting is usually completed as part of the associated action plan. Hence, these budget requirements will be considered at an early stage of planning. D. Data governance and oversight Governance framework Similar to other organizational functions, the maturity of governance approaches managing data as a strategic asset will evolve into the systematic level, where data is central to all strategies, drives innovation, is integrated across data ecosystems, and delivers optimal value for the organization. 26 This is achieved by consolidating data governance best practices gradually developed by ESCWA clusters, offices, units and teams at the foundational level of strategy implementation. As trial and error are part of the journey, the result will be a holistic data governance framework at ESCWA, developed by the Data Strategy Action Group that benefits from lessons learned and aligns with the core governance parameters outlined in the Secretary-General’s Data Strategy. Strategy oversight and tracking To catalyse progress, it is recommended to adhere to a hybrid implementation approach, where decentralized teams cooperate with each other and with senior managers to realize a commissioned set of data activities. Broadly put, the Data Strategy Action Group will ensure action at every level by setting and overseeing strategy implementation priorities. This cross-cutting approach constructs a balance between identifying potential data use cases in the ESCWA context and responding to overall organizational priorities; and ensuring strategy oversight does not morph into trade-off decisions among innovative ideas. In addition to providing strategic direction, a key activity for the Action Group in implementing this strategy is regularly measuring progress towards the objectives articulated in the “value statement” section. Target metrics capturing both the impact and progress need to be established at the outset of the data strategy by the Data Strategy Action Group. Tracking for impact can be achieved via the data, digital and innovation parameters surveyed at the ESCWA level by the annual United Nations Innovation Network (UNIN) capacity mapping. Progress tracking should primarily consider the following metrics: • The completion rate of the tasks outlined in the operational action plan (Gantt Chart) • The indicators underlined in the Secretary-General’s Data Strategy in the “recommendations and next steps” section Data governance at ESCWA is composed of, but not limited to, the following: 1. Data strategy implementation action plan; 2. Data Strategy Action Group; 3. UNIN annual survey; 4. Secreatry-General’s data strategy recommendations. Figure 9. Secretary-General’s approach to delivering data action portfolios Clarify Priorities Drill down to outcomes Identify use cases Evaluate use cases Evaluate case portfolio Deliver portfolio 27 Intellectual property Data is a set of “factual” information generated from various streams, collected and processed by a controller. In the broad sense, this renders data not copyrightable because it is discovered, not created as original works.6 In specific, this strategy encourages ESCWA to copyright the compilation processes of data and new “data” based on collected information, while at the same time referencing the source of data used. This becomes especially true as ESCWA is starting to tap open data and big data, requiring data sharing policies that prioritize open data distribution. ESCWA is also investigating ways to mobilize the power of machinegenerated data. Technology integration is providing novel data sources and myriad opportunities to harness the transformative power of data: Traditional and Big Data. For example, AI can be the tool to uncover untold stories, and extract foundational insights and actionable information from the growing datasets. Although it is the early days for data technologies, ESCWA will factor in the possibility of copyrighting the innovative tools ESCWA develops during the data-influenced transformation with the willingness to support member countries within the context of innovative statistical solutions. Moreover, ESCWA is determined to unlock breakthroughs to pressing challenges and promote data-driven decision-making. As such, patent law may be applicable if ESCWA data compilation, and subsequent processing, yields new insights or solutions to precisely defined problems. E. Partnerships The data transformation roadmap at ESCWA should not be performed in a silo. It should be a participatory effort benefiting from a large community of experts and specialists, to avoid duplication of efforts. ESCWA can build effective partnerships for initiatives that require external practical expertise and knowledge to drive internal data innovation at all stages of our roadmap, especially at the transformational stage. The critical success factor to effectively learn from – and utilize the collective intelligence of – those we work with is to engage in partnerships when the intricacies of a particular data initiative can be handed over to experienced agencies in that domain. To that end, buy-in is required by the whole ESCWA staff to identify partnership opportunities and eventually be delegated to coordinate the collaboration. Moreover, senior management at ESCWA must proactively articulate a precise and concrete set of goals for their offices reflecting the present data strategy’s overall vision. Partnerships for technology and data solutions require explicit concrete goals; clear cooperation guidelines; and adequate risk mitigation actions. Identifying such baselines will streamline the co-creation of solutions, with the flexibility to update them as necessary in the light of technology changes and greater capabilities. The following organizations, from the United Nations system, member States, and private sector, are potential partners in implementing a sound data strategy. 28 Table 3. Possible partnerships and collaborators for data strategy implementation Organization/entity Possible cooperation OICT Assist ESCWA in technology adoption and technical innovation CEB Act as the steering body regarding high-level data governance and oversight for both the secretariat and entities ICTP Provide technology infrastructure and superstructure, and enhance connectivity and resilience UNSSC Provide custom-tailored learning solutions for ESCWA during the implementation of the data strategy Data Strategy Hub Act as an idea repository and learning and news platform for the system-wide implementation of the Data Strategy of the Secretary-General DOS Offer tangible recommendations at the entity level DMSPC Offer advisory to the implementation of both the Data Strategy of the SecretaryGeneral and its subsets (working papers, surveys, best practices, etc.) Data Governance Provide follow-up and guidance on the implementation of the Data Strategy of the Group Secretary-General CSS-UN Streamline statistical initiatives and vision across the secretariat LAS, Arab ECOSOC Exchange know-how and capacity-building Required actions _________ The following are actionable recommendations for effective implementation of the activities prescribed in the present strategy, set out for execution by different offices and teams at ESCWA: 1. Form a data strategy action group to oversee the implementation of this Strategy. 2. Derive a data strategy implementation action plan. 3. Revisit generic job descriptions at ESCWA to reflect data priorities. 4. Gradually develop an ESCWA analytical model base. 5. Fund allocation for data technology procurement. 6. Re-enforce technology infrastructure and connectivity capabilities. 7. Facilitate data strategy implementation through training, hiring and policy communication. 8. Invest in cyber-security for technology systems such as a database with sensitive data. 9. Develop legal and ethical guidelines for intellectual property, open data, and relevant data-related behavioural issues. 10. Harmonize ESCWA data work with the overall United Nations system by complementing related efforts. 11. Enhance data management and data governance in a horizontal structure across ESCWA clusters and with the wider United Nations system. 12. Retire, or upgrade when possible, legacy technologies at the core of existing data programs restricting holistic data sharing and utilization. 29 Strategy deliverables _________ The following are spin-off deliverables of the present strategy: 1. The operational action plan outlining the high-level actionable tasks that are required to execute the stipulations of the strategy and the task assignment to resources as the timetable for execution. 2. The sample taxonomy of ESCWA knowledge and data production. 3. The envisaged data-related job posts required to successfully implement the strategy. 4. The recommended governing approach for an ESCWA-wide model base and the model register template. 5. An operational data ecosystem framework for data analytics, platform utilization, and visualization. 6. List of recommended agencies to partner with during implementation. 7. The recommended ethics, data protection and security organogram at ESCWA. 30 Annex I. Examples of ESCWA statistical and interregional cooperation activities ESCWA provides statistical and data services to member States ESCWA statistical activities address a wide range of statistical domains and subject-matter areas, spanning economic statistics, population and social statistics, and statistics on natural resources. In the area of economic statistics, ESCWA addresses the implementation of the System of National Accounts (SNA). The core requirements of the 2008 SNA were implemented by all ESCWA member States. This work also includes aligning concepts of Islamic banking with SNA data reporting. ESCWA also works on social accounting, which contributes to policy analysis undertaken by ESCWA. Work on financial statistics includes balance of payments, government finance, and price indices. For prices, ESCWA assists member States in producing consumer price indices to achieve achieved a harmonized pan-Arab consumer price index. Moreover, ESCWA is the regional implementing agency of the International Comparison Programme (ICP), which calculates the annual values of purchasing power parities (PPPs). The United Nations Statistical Commission called upon the ICP implementing agencies to continuously integrate ICP in their regular statistical activities. In the production of price indices, ESCWA also promotes the use of alternative data sources for collecting raw data on consumer baskets, such as web-scraping and the use of scanner data. Economic sectoral statistics include work on external trade statistics, where ESCWA is the main source of data for Arab countries on bilateral trade and commodities at the six-digit level of the Harmonized System. ESCWA has succeeded in improving data quality and resolving gaps by complementing data collected from Arab countries with data from the rest of the world, and mirroring trade flows from data reported by trade partners. ESCWA data on external trade are currently loaded into the ComTrade database of the United Nations. ESCWA has also a unique role in producing a regional data set on industrial production and resources, including employment. At ESCWA, energy statistics are considered to be closely related to the environment and natural resources statistics. ESCWA works on methodological enhancements with national statistical offices, and on data collection in collaboration with the International Energy Agency of the OECD and the United Nations Statistics Division. Following UN Mandates and a respective request by its Statistical Committee, ESCWA began compiling and disseminating transport statistics for the Arab region. Currently, the data compiled covers road transport, railway transport, marine transport, air transport, and SDG-related transport indicators for road safety. Similarly, the modes of transport data are also considered and include 31 infrastructure, equipment, and economic measures. These modes are disaggregated, whenever possible, by type, sex, and age. More recently, ESCWA is working closely with the Arab states to develop partnerships with regional and international organizations in the field of transport statistics, such as UNECE, MEDSTAT and ITF, to collaborate on technical papers and guidelines, methodology, and standardsetting; with the impetus to strengthen future collaboration. ESCWA is also exploring ways to use alternative and complementary data sources and analysis in transport statistics, including big data. Regarding economic statistics, capacity development activities include promotion and assistance in widening the use of statistical business registers in the Arab region as a sampling frame for economic surveys, and developing urban observations in close coordination with local governments to collect local data and statistics to better tackle issues that are traditionally difficult to address, such as the informal economy which represents a sizable share of the economies of most Arab countries. Demographic and social statistics activities include work on population estimates and the use of civil registration for vital statistics. In the area of population and housing censuses, ESCWA works with national statistical offices on increased use of advanced technologies in census preparations, management and data collection, and on linking census data with geospatial information. In the ongoing 2020 census round, which has been delayed owing to the COVID-19 outbreak, there is an increased use of administrative registers and records as a source of census data, in particular in GCC member States. ESCWA also works with national statistical offices on increasing the use of census results in further statistical production, especially in the production of SDG indicators. The range of social indicators addressed by ESCWA include education, labour, health, poverty, and cross-cutting social indicators, including the core set of social indicators in the context of sustainable development. ESCWA also cooperates with the Food and Agriculture Organization of the United Nations on data and statistics related to food security. While it has a strong social aspect, the area of gender statistics is considered a cross-cutting issue at ESCWA. ESCWA has developed a successful curriculum on gender statistics, part of which is online training, whose enrolments have already exceeded 12,000 trainees. ESCWA has also achieved significant progress in disability statistics in data collection and production, and in building capacity of national statistical systems. The regional handbook on disability statistics, which is based on the concepts and approaches of the Washington Group on Disability Statistics, is the first regional handbook of its kind. Further work is needed to implement the handbook, and to achieve a higher level of data availability, especially for data collected through censuses and household surveys. For environment and natural resources statistics, ESCWA work focuses on water resources and use and the environment (related to pollution and land use). ESCWA assists national statistical systems in implementing the System of Environment Economic Accounting. In collaboration with international partners, such as Eye on Earth and the United Nations Environment Programme, ESCWA is engaged in statistics on natural disasters, notably in implementing the Sendai Framework. 32 Inter-regional cooperation on statistics and data In the context of SDG progress assessment, the statistics divisions of the United Nations regional commissions worked on harmonizing methods for data interpretation and presentation. Their common approach (the progress traffic lights) uses three colours (green, yellow and red) indicating progress. Three levels of visualization are used for Goals 1-17, with bars expressing progress since 2000; targets, based on predictions of 2030 values, indicating how likely the target will be achieved; and indicators showing the gap between the predicted and target values. The regional commissions prepared a joint presentation for several events taking place in 2020. The selection of indicators was based on common criteria and the ability to set target values and clear metadata explaining the indicator. Two different measures are used to assess progress: on track/not on track. The Current Status Index is based on where the region (and subregions) currently stand on the Goals. The Anticipated Progress Index shows how likely the region (and subregions) will achieve individual SDG targets, judging by the pace of progress thus far. The statistics divisions of the United Nations regional commission hold weekly virtual coordination meetings, focused on coordinating the structure and representation of SDG-related knowledge products. Approaches to regional reforms are also discussed at these meetings, especially the coordination of statistical activities at the regional level within regional cooperation platforms, and collaboration between the regional statistics divisions and the United Nations country teams. In 2021, inter-regional coordination on SDG data and statistics will also involve the United Nations Statistics Division (UNSD) to harmonize the presentations of SDG indicators at the regional and global levels. In recent years, UNSD and the regional statistics divisions have held bi-monthly coordination meetings covering key topics of statistical programmes and global and regional events. The statistical ecosystem in the Arab region must be aware of United Nations data strategies and policies, and use such literature as guidance to align their national statistical priorities with overall regional statistical development. Moreover, such priorities should consider the use of advanced technologies for the automation of data interchange, and for linking statistical and geospatial information. 33 Annex II. Suggested ESCWA high-level modelling governance framework Consult the model base If the model exists: present Evaluate the model as per the intended use case If insufficient to project needs If not: Propose a model Approval rejected Select the model Wait for approval Approval granted Add a model Contact model steward for details Update model base details as per the template Novel challenges exhibited Utilize the selected model Update model base 34 Annex III. High-level Data and Technology Ecosystem Source: 365 Data Science Team, Defining Data Science: The What, Where and How of Data Science, 2021. 35 Annex IV. ESCWA data solutions ESCWA Data Solutions 3 Demographic and social data • Population statistics • Poverty statistics • Labour statistics • Education statistics • Health statistics • Inequality statistics 4 Leave No One Behind (LNOB) • Disability statistics • Gender statistics • Aging statistics • Youth Statistics • Government electronic and mobile services (GEMS) 2 Economic Data • National Accounts • Finance statistics • Industry statistics • Trade statistics • Transport statistics • Purchasing Power Parities Economic Social LNOB DATA PORTAL Personalised Profiles for UNCTs Environmental 5 Natural resources data • Environment statistics • Energy statistics • Water statistics • Climate statistics • Food Security statistics SDGs 1 SDG Data and Statistics • SDG indicators database • SDG regional analysis - monitor • SDG National Reporting Platform SD G Data Regional U N 203 Cou United N ntry level SDG Data 0 DaattioansPGrloobgarl ess VoluanntDadartyaAsNneatatiloynsailsReviews e d Nationally Report Big Data & Open Data Secretary General's Data Strategy Global UN Data National Statistical Offices (NSOs) Interactive Simulation Tools 36 Annex V. High-level operational action plan To be produced after finalizing the Strategy by the Data Strategy Action Group 37 Annex VI. Terms of reference of ESCWA data privacy and security roles The table sets out the terms of reference of the of ESCWA data privacy and security roles, as put forward at the seventh meeting of the Executive Committee.7 Table 3. Possible partnerships and collaborators for data strategy implementation Data position/role Terms of reference Data steward/controller • Ensure ST/SGB compliance on behalf of the Secretary-General; • Designate entity data protection focal points by 30 June; • Oversee the purposes, content, use, and means of data processing in their entity or cross-cutting enterprise function; • Manage exceptions to data policies; • Facilitate the use of data assets within the organization. Data protection focal points • Consult with OIOIS to identify, support – and where necessary cost – priority changes in organizational processes and practices and software applications used for programmes and operations; • Consult with OICT to identify data inventory/catalogue solutions to ensure relevant data assets can be registered, managed, and identified by 30 September; • Facilitate the day-to-day implementation of data activities put forward by the Data Management Officer; • Coordinate with the Secretariat Data Protection Officer. Data operators • Utilize data in the entity’s data initiatives and use cases. 38 Endnotes 1. J. Gallant and K. Fleet, The Data Strategy Playbook, commissioned by Informatica. 2. United Nations Innovation Network, UN System Capacity Mapping 2020: Innovation, Data and Digital Capabilities, United Nations, February 2021. 3. Executive Office of the Secretary-General, Memorandum – Data Strategy Implementation: Actions for building data skills and talent, 3 February 2021. 4. Department of Operational Support, Implementing the Data Strategy Through Workforce Planning, p. 6, April 2021. 5. EOSG, DOS and DMSPC, draft – Data Strategy Virtual Sessions | FAQs, 13 April 2021. 6. Kent State University, Data Management: Intellectual Property and Copyright, University Libraries. Available at https://libguides. library.kent.edu/data-management/copyright. 7. Data Governance Group of the United Nations, Roadmap and Programme of Work, Data Protection and Privacy Programme, Briefing Paper, March 16/18, 2021. 21-00433
关注微信
